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    Machine Learning Engineer - Pittsburgh, United States - Mastech Digital

    Mastech Digital
    Mastech Digital Pittsburgh, United States

    3 weeks ago

    Default job background
    Description

    Mastech Digital Inc. is a (certified )Minority owned business certified by NMSDC. Public traded firm under MHH at NYSE, Established in 1986. Headquartered in Pittsburgh, PA our operations are spread across 11 Global Recruiting & Sales offices across US.

    Hit Apply below to send your application for consideration Ensure that your CV is up to date, and that you have read the job specs first.

    Job Title: Machine Learning Engineer

    Job Category: Software Development/ Engineering

    Job Type: Permanent Full Time

    Location: Pittsburgh, PA, Strongsville, OH (Cleveland)

    Your future duties and responsibilities

    • Design various enterprise information and data and analytics strategies, including defining visions, conducting assessments of people, processes, and technology; and developing dynamic business value roadmaps.
    • Design and implement modern industry best practices in governance, management, and quality of information/data.
    • Design and implementation of data quality scorecards and metrics.
    • Evaluation, selection and implementation of tools and technology for data catalogs, data governance, data quality and data management.
    • Collaborate with business and technical teams to provide direction for and contribute to development, implementation and rollout of solutions and consulting services.
    • Facilitate design and solution workshops with clients.

    Required qualifications to be successful in this role:

    • 3-6 years of experience in
    • Model building, Machine Learning Ops, API's, Python, Jenkins, OCP
    • Machine Learning & Data Engineering pipelines
    • Python with Django and Flask, Spark, Big-Data stack - Hive< Kafka & NoSQL's
    • ML Frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
    • Statistical Analysis and Fine-Tuning/Hyper-Tuning the models (like Spark-Trails, Optuna).
    • Model Lifecycle management in ML Flow and Graph QL
    • Feature Engineering
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